Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation

26 January 2023

Papers citing "Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation"

7 / 7 papers shown

Title
Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics Elena Camuffo Umberto Michieli Simone Milani J. Moon Mete Ozay 33 0 0 08 Jul 2024
Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse Data Elena Camuffo Simone Milani 3DPC CLL 13 8 0 08 Apr 2023
PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences Hehe Fan Xin Yu Yuhang Ding Yi Yang Mohan S. Kankanhalli 3DPC 112 108 0 27 May 2022
LatticeNet: Fast Spatio-Temporal Point Cloud Segmentation Using Permutohedral Lattices R. Rosu Peer Schütt Jan Quenzel Sven Behnke 3DPC 31 32 0 09 Aug 2021
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation Aoran Xiao Xiaofei Yang Shijian Lu Dayan Guan Jiaxing Huang 3DPC 19 47 0 01 Mar 2021
Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks Kirill Mazur Victor Lempitsky 3DPC 40 39 0 22 Jul 2020
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 210 13,886 0 02 Dec 2016